Optimal discrete model reduction by multipoint Padé approximation

T. Nigel Lucas

doi:10.1016/0016-0032(93)90081-5

Optimal discrete model reduction by multipoint Padé approximation

T. Nigel Lucas

Research output: Contribution to journal › Article

16 Citations (Scopus)

Abstract

A discrete-time multipoint Padé approximation method is presented that derives optimal reduced-order models. The method is seen to be easily implemented using a recently developed way of calculating Padé approximants. An important result that relates the optimal model to multipoint Padé approximation is proved and the whole process isseen to consist of multiplying matrices and solving linear equations. Numerical examples are given to illustrate the application of the new method.

Original language	English
Pages (from-to)	855-867
Number of pages	13
Journal	Journal of the Franklin Institute
Volume	330
Issue number	5
DOIs	https://doi.org/10.1016/0016-0032(93)90081-5
Publication status	Published - Sep 1993

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Lucas, T. N. (1993). Optimal discrete model reduction by multipoint Padé approximation. Journal of the Franklin Institute, 330(5), 855-867. https://doi.org/10.1016/0016-0032(93)90081-5

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abstract = "A discrete-time multipoint Pad{\'e} approximation method is presented that derives optimal reduced-order models. The method is seen to be easily implemented using a recently developed way of calculating Pad{\'e} approximants. An important result that relates the optimal model to multipoint Pad{\'e} approximation is proved and the whole process isseen to consist of multiplying matrices and solving linear equations. Numerical examples are given to illustrate the application of the new method.",

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AB - A discrete-time multipoint Padé approximation method is presented that derives optimal reduced-order models. The method is seen to be easily implemented using a recently developed way of calculating Padé approximants. An important result that relates the optimal model to multipoint Padé approximation is proved and the whole process isseen to consist of multiplying matrices and solving linear equations. Numerical examples are given to illustrate the application of the new method.

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